Random Forest Regressor
This module belongs to the " Machine Learning algorithms" category.
Last updated
This module belongs to the " Machine Learning algorithms" category.
Last updated
This module is a parameterizable and trainable Random Forest regression model.
It contains functions to variate the sample leaf nodes, impurity, features and depth, just like the Random Forest Classifier.
For forecasting accuracy , as criteria of measure, we have the choice between mse (stands for : mean squared error ) and mae (mean absolute error) . (for more details refer to Sci-kit metrics )
whereas features can be :
auto,
SQRT
Log2
Integer
Float
None
